The concrete recycling industry faces significant challenges due to the uncontrolled mixing of parent concretes with varying properties during demolition, resulting in inconsistent recycled concrete aggregate (RCA) quality and limiting its potential for use in new concrete production. Existing literature typically characterizes parent concrete solely based on compressive strength, neglecting other critical parameters. Consequently, RCA is often labelled as inherently heterogeneous, without fully considering the variability introduced by mixed-source demolition. This study introduces an novel protocol for systematic parent concrete characterization, combining an Artificial Intelligence (AI)-based segmentation approach with complementary techniques like polarized light and fluorescence microscopy (PFM). The proposed methodology quantifies critical properties of parent concrete, including water-to-cement (W/C) ratio, cement and aggregate content, air void content, and aggregate gradation. This enables a detailed evaluation of parent concrete variability, providing the basis for selective demolition strategies that reduce RCA heterogeneity and enhance the predictability of its properties. To illustrate its applicability, the protocol was applied to structural components of a Dutch viaduct, including prestressed beams, heavily reinforced columns, foundations, and abutment-wall. Results revealed significant differences in estimated water-to-cement ratios, ranging from 0.29 ± 0.03 in beams to 0.38 ± 0.03 in abutment walls, while hydration degrees varied between 0.80 ± 0.08 and 0.93 ± 0.02, indicating differences in cement maturity. Cement content ranged from 316 ± 11 kg/m³ in foundations to 390 ± 10 kg/m³ in beams, and air void content ranged significantly from 0.9 % in abutment walls to 4.3 % in foundations. Microstructural composition also differed substantially: paste volume ranged from 17 % to 27 %, and coarse aggregate content from 37 % to 52 % depending on the component. These quantitative differences confirm that structural concretes, even within the same structure, exhibit substantial internal variation. As such, uncontrolled demolition leads to the mixing of materials with fundamentally different properties—supporting the argument that RCA heterogeneity is not intrinsic, but largely a result of conventional demolition. This reinforces the value of the proposed protocol in identifying material variability and informing targeted demolition to enhance the predictability and uniformity of RCA.

Due to the gradual diffusion of CO₂ under natural exposure, areas with varied degrees of carbonation exist at different depths from the surface of slag-rich cement paste. While extensive research has been dedicated to investigating the fully carbonated zone as identified by phenolphthalein spray, the transitional zone, located between the fully carbonated and the uncarbonated regions, has received comparatively less attention. This study thus aims to address this research gap by exploring its microstructural, micromechanical, and mineralogical properties. The results reveal that carbonation-induced damage extends beyond the fully carbonated zone as identified by phenolphthalein. Particularly in the transitional area close to the carbonated zone, nanoindentations results reveal that micromechanical properties of this area are even lower to that of the fully carbonated zone. In addition, mineralogical investigation suggest that the depth of carbonation stays within the range where slag-containing blends loses its green coloration. By comparing specimens with different slag composition, it was found that the depth of this faded green area can be an important indicator to assess the carbonation resistance of slag-containing blends.

Structural fatigue can lead to catastrophic failures in various engineering applications and must be properly monitored and effectively managed. This paper provides a state-of-the-art review of recent developments in structural fatigue monitoring using piezoelectric-based sensors. Compared to alternative sensing technologies, piezoelectric sensors offer distinct advantages, including compact size, lightweight design, low cost, flexible formats, and high sensitivity to dynamic loads. The paper reviews the working principles and recent advancements in passive piezoelectric-based sensors, such as acoustic emission wave and strain measurements, and active piezoelectric-based sensors, including ultrasonic wave and dynamic characteristic measurements. These measurements, captured under in-service dynamic strain, can be correlated to the remaining structural fatigue life. Case studies are presented, highlighting applications of fatigue life monitoring in metals, polymeric composites, and reinforced concrete structures. The paper concludes by identifying challenges and opportunities for advancing piezoelectric-based sensors for fatigue life monitoring in engineering structures.

The buckling mode in piezoelectric materials offers advantages such as an increased measurable strain range, ease of installation, and extended service life. This paper investigates the potential of piezoelectric sensors operating in buckling mode for structural strain measurement by evaluating key factors including boundary conditions, sensor response linearity under dynamic loading, and impedance engineering to optimize the voltage–strain relationship. A structural extension was developed to facilitate sensor integration and to enable the application of different buckling boundary conditions. Results show that the clamped–clamped configuration generated at least 1.65 times higher output voltage, and three times greater peak strain compared to other boundary conditions. An experimentally validated analytical model was employed to assess and improve the performance of buckled piezoelectric sensors in dynamic environments. The findings highlight that introducing initial buckling reduces signal perturbations, enhances voltage linearity across loading frequencies, and extends the effective strain measurement range. Furthermore, impedance engineering was used to successfully mitigate the nonlinear effects of transient response, thereby improving signal stability and accuracy in dynamic strain monitoring applications.

This study evaluates the performance of damaged concrete beams retrofitted with a purpose-designed mechanochromic composite, which provides structural reinforcement and visual feedback for structural health monitoring (SHM). The retrofitting process utilizes externally bonded reinforcement (EBR) on pre-damaged concrete prisms. The mechanochromic composite, a thin-ply hybrid material made of unidirectional ultra-high modulus (UHM) carbon/epoxy and S-glass/epoxy layers, changes color to indicate structural overload when the UHM carbon layer fractures due to excessive strain. Eighteen concrete specimens were prepared and subjected to four-point bending tests, assessing various combinations of damaged, undamaged, retrofitted, and non-retrofitted configurations. Results showed that the mechanochromic composite functions effectively as both a passive visual sensor and reinforcement. For instance, a 5 % crack depth reduced load-bearing capacity by 30 %, however, retrofitting with the mechanochromic composite improved load-bearing capacity by up to 208 % compared to undamaged beams. The study further discusses the effects of different damage levels on load-bearing capacity through flexural strength, load-displacement curves, and failure modes.

Anisotropy in 3D-printed concrete structures has persistently raised concerns regarding structural integrity and safety. In this study, an architected 3D printing strategy, “stitching”, was proposed to mitigate anisotropy in 3D-printed Engineered Cementitious Composites (ECC). This approach integrates the direction-dependent tensile resistance of extruded ECC, the mechanical interlocking between three-dimensional layers, and a deliberately engineered interwoven interface system. As a result, the out-of-plane direction of the printed structure can be self-reinforced without external reinforcements. Four-point bending tests demonstrated that the “stitching” pattern induced multi-cracking and flexural-hardening behavior in the out-of-plane direction, boosting its energy dissipation to 343 % of the reference “parallel” printing and achieving 48.6 % of cast ECC. Additionally, micro-CT scanning and acoustic emission tests further validated the controlled crack propagation enabled by the engineered interface architecture. The proposed strategy has been proven to substantially alleviate anisotropy and enhance structural integrity.

Accurate and reliable strain measurement is essential for effective condition monitoring of engineering structures. This study presents an analytical and experimental investigation into the performance of piezoelectric sensors for structural strain measurements, evaluating the effect of attachment strategy and the properties of the substrate and the sensor. Lead zirconate titanate (PZT) and polyvinylidene fluoride (PVDF) sensors were evaluated in two attachment configurations: Fully Attached (FA) and Two-End Attached (TEA). A voltage-strain relationship was developed based on principles of piezoelectricity, electrical circuit modelling, and solid mechanics. Results indicate that sensor performance is significantly influenced by the attachment method. Specifically, the TEA configuration reduced the impact of substrate properties and improved uniaxial strain measurement accuracy by up to 32 % compared to the FA configuration. The FA configuration exhibited sensitivity to the substrate's Poisson ratio, leading to a nonlinear voltage-strain response. In contrast, the TEA configuration provided pure uniaxial strain measurements by reducing the effects of shear lag and substrate elasticity. These findings provide a comprehensive approach to using piezoelectric sensors for structural strain measurement, allowing for the placement of sensors on various substrates without the need for calibration by effectively utilizing sensor and substrate properties along with the attachment strategy. The study provides a novel analytical–experimental comparison of sensor attachment methods, showing how TEA significantly improves uniaxial strain accuracy and reduces substrate dependency in piezoelectric strain measurements.

Portland cement paste has a highly heterogenous evolving microstructure that complicates the development of stronger and greener cementitious materials. Microstructure is the fundamental input of multiscale studies on material behaviors. Herein, we propose a conditional generative AI framework for synthesizing high-fidelity 3D microstructures of hydrating cement paste (1–28 days) with varying water-to-cement ratios and Blaine fineness values. A latent diffusion transformer, operating within a compact two-stage latent space derived via a vector quantized variational autoencoder, efficiently captures and reproduces experimentally measured microstructural patterns. Statistical analyses confirm strong consistency in grey value distributions, micromechanical properties, hydration phase evolution, and particle size distributions, with only minor boundary-related discrepancies. Validation using a pretrained classifier further corroborates the fidelity of generated microstructures. This approach provides a robust tool for realistic cement paste microstructure generation, supporting multiscale modeling and advancing the design of sustainable cementitious materials.

This paper reports the development, optimization, and real-world application of an innovative wobbling triboelectric nanogenerator to harvest energy from wind or vibrations. The harvester features a spring-supported structure, purposely designed to become unbalanced and reversibly shift from a steady to a non-steady state in response to minimal wind or vibration stimuli. Unlike conventional wind turbines, this approach transforms wind energy into contact-separation events via a wobbling structure. The harvester’s mechanisms are engineered to enhance power generation efficiency, optimizing parameters like electrode dimensions and contact-separation quality. Experimental findings showcase a maximum output power density of 1.6 W/m2 under optimal conditions, employing a fixed suspending mechanism for heightened impact energy during contact. Moreover, the harvester efficiently charges a 3.7 V lithium-ion battery with over 4.5 μA, showcased in a self-powered light mast as a practical demonstration. The harvester provides cost-effectiveness by utilizing inexpensive, easily accessible materials without complex fabrication. This research paves the way for future exploration in integrating triboelectric nanogenerators with wobbling mechanisms, offering a promising pathway for sustainable power generation across various applications, including lighting and IoT sensor nodes.

Auxetic cementitious cellular composites (ACCCs) exhibit hinge-type recoverable deformation during auxetic behavior phase, a rare pseudo-elastic property in cementitious materials. However, their low load-bearing capacity during this phase restricts their use in high-load applications. This study developed ACCCs using strain-hardening cementitious composites (SHCCs) with short (SHCC-SS) and long (SHCC-LS) softening tails, fabricated by additive manufacturing-assisted casting. Uniaxial compression tests employing Digital Image Correlation (DIC) evaluated their compressive behavior, peak strength, Poisson's ratio variation, and energy dissipation. Cyclic tests after pre-compression assessed their recoverable deformation resilience, with fiber bridging at joint cracks examined using digital optical microscope. Results were compared to a reference using fiber-reinforced cementitious materials with strain softening (SS). Compared to the reference (SS), ACCCs using SHCC mixtures exhibit superior load-bearing capacity and stable auxetic behavior under compression. After self-contact, they maintain a negative Poisson's ratio up to a considerably high compressive strain, preventing splitting failure and preserving structural integrity. This is because incorporating SHCC enables greater joint rotation by promoting multiple cracks with strain hardening, which delays primary crack formation and reduces its opening. During cyclic tests, P1-shaped ACCCs with SHCC-LS and SHCC-SS enhance the elasticity modulus of recoverable deformation by 4.8 and 3.0 times, respectively, compared to SS. SHCC-LS outperforms SHCC-SS in compressive resilience due to its prolonged softening tail, which improves fiber bridging in primary cracks and increases rotational stiffness in hinge joints. SHCC mixtures with initial strain hardening and extended softening enable scalable design of advanced auxetic cementitious materials across various load levels.

Self-healing concrete, with its ability to autonomously repair damages, holds promise in enhancing its structural durability and resilience. Research on self-healing concrete in the past decade has advanced in understanding the mechanisms behind healing, exploring various healing agents, and assessing their effectiveness in concrete structures. However, the full potential of self-healing concrete remains untapped unless its effects are effectively integrated into the design practices of reinforced concrete structures. Realizing this challenge, this paper synthesizes the current research progress and discusses the possibilities to consider self-healing into design codes. The focus was placed on two specific benefits of applying self-healing concrete: one centered on durability and the other on mechanical performance. Specifically, the effect of self-healing on impeding chloride penetration into cracked reinforced concrete was discussed first. Modifications of parameters in existing predictive models based on different types of healing approaches were recommended. Furthermore, the possible impact of the self-healing capacity in mitigating the stiffness reduction of concrete was also discussed. Equations that can describe the stiffness regained due to healing action are presented. In each part of the case study, limitations and challenges still hindering standardization and wider application in the construction field are discussed.

The microstructure of cement paste determines the overall performance of concrete and therefore obtaining the microstructure is an essential step in concrete studies. Traditional methods to obtain the microstructure, such as scanning electron microscopy (SEM) and X-ray computed tomography (XCT), are time-consuming and expensive. Herein we propose using Denoising Diffusion Probabilistic Models (DDPM) to synthesize realistic microstructures of cement paste. A DDPM with a U-Net architecture is employed to generate high-fidelity microstructure images that closely resemble those derived from SEM. The synthesized images are subjected to comprehensive image analysis, phase segmentation, and micromechanical analysis to validate their accuracy. Findings demonstrate that DDPM-generated microstructures not only visually match the original microstructures but also exhibit similar greyscale statistics, phase assemblage, phase connectivity, and micromechanical properties. This approach offers a cost-effective and efficient alternative for generating microstructure data, facilitating advanced multiscale computational studies of cement paste properties.

Self-healing cementitious materials show potential to reduce material consumption, maintenance costs, and environmental impacts within the construction sector. This study explores the feasibility of installing a ductile-porous vascular network in a series of retaining walls under realistic construction conditions, with the objective of both assessing the efficacy of the self-healing system and addressing any constructability issues that may arise. Numerical modelling was performed first to determine a suitable mix design and wall configuration that would promote cracking, so cracks would appear without mechanical intervention. The predicted crack distribution informed the optimal network configuration. Healing and sustainability considerations are discussed, and the benefits of implementing this technology are evaluated. When comparing a single maintenance activity using a vascular network versus manual repair, there is no significant benefit of using a vascular network. However, environmental impacts are substantially reduced when using a vascular network once multiple repair actions are considered.

Early-age cracking risk induced by autogenous deformation is high for cementitious materials of low water-binder ratios. The autogenous deformation, viscoelastic properties, and stress evolution are three important factors for understanding and quantifying the early-age cracking risk. This paper systematically reviewed the experimental and modelling techniques of the three factors. It is found that the Temperature Stress Testing Machine is a unified experimental method for all these three factors, with a strain-controlled mode for stress evolution, hourly-repeated loading scheme for viscoelastic properties, and free condition for autogenous deformation. Such unified method provides basis for developing various models. By coupling a hydration model for volume fractions of hydrates, a homogenization model for upscaling of viscoelastic properties, and capillary pressure theory for self-desiccation shrinkage, a unified model directly mapping the mix design to the early-age stress can be constructed, which can help optimize the mix design to reduce the early-age cracking risk.

Engineering structures, such as bridges, wind turbines, airplanes, ships, buildings, and offshore platforms, often experience uncertain dynamic loadings due to environmental factors and operational conditions. The lack of knowledge about the load spectrum for these structures poses challenges in terms of design and can lead to either over-engineering or catastrophic failure. This research introduces a robust and innovative device, analogous to a "Fitbit" for structures, capable of measuring complex loading conditions throughout the structure's lifespan. The proposed approach involves developing a middleware, referred to as an "extension," which facilitates the transfer of mechanical deformation to a piezoelectric sensor. This approach overcomes challenges associated with directly attaching piezoelectric sensors to the structure's surface such as rupture possibility in higher strain and attaching on rough surfaces. The feasibility study primarily focuses on validating the performance of the extension and monitoring variation trends. The ultimate objective is to develop an Internet of Things (IoT) sensor node capable of measuring applied cyclic loads. To achieve this goal, an electronic system and embedded software will be developed to capture the complex load spectrum and convert it into a fatigue damage index for predicting the structure's fatigue life. The collected data will be transmitted to the user through a wireless communication platform. The proposed sensor design is versatile, allowing for both attachment and embedding and is demonstrated here for monitoring fatigue in engineering structures.

This paper presents a state-of-the-art review on the application of additive manufacturing (AM) in self-healing cementitious materials. AM has been utilized in self-healing cementitious materials in three ways: (1) concrete with 3D-printed capsules/vasculatures; (2) 3D concrete printing (3DCP) with fibers or supplementary cementitious materials (SCMs); and (3) a combination of (1) and (2). 3D-printed capsules/vascular systems are the most extensively investigated, which are capable of housing larger volumes of healing agents. However, due to the dimension restraints of printers, most of the printed vasculatures/capsules are in small scale, making them difficult for upscaling. Meanwhile, 3DCP shows great potential to lower the environmental footprint of concrete construction. Incorporation of fibers and SCMs helps improve the autogenous healing performance of 3DCP. Besides, 3D-printed concrete with hollow channels as the vasculature could further improve the autonomous healing and scalability of self-healing cementitious materials. Finally, possible directions for future research are discussed.

The present paper reports an overview of mechanochromic self-reporting thin-ply hybrid composite sensors, which are designed to visually indicate overload in structures. These sensors, made from combinations of high-strain and low-strain materials, change appearance earlier than the final fracture, providing a clear visual cue of damage like delamination or strain overload. They can be used for various applications, for example, overload monitoring, and to detect barely visible impact damage in composites.

This study investigates the structural behaviour and self-healing performance of hybrid reinforced concrete (RC) beams, enhanced with a 1.5-cm-thick self-healing cover composed of bacteria-embedded strain hardening cementitious composite (SHCC), for its potential in crack width control and crack healing. The research focuses on the performance under both flexural and shear loading, examining aspects such as load-bearing capacity, surface crack pattern, crack propagation between layers, and healing effectiveness. Results demonstrate the successful activation of the healing function, alongside improvements in structural performance. Under flexural loading, hybrid beams exhibited greater load-bearing capacity and significantly improved crack control ability. The maximum crack width of the hybrid beams exceeded 0.3 mm at 124.7 kN load, whereas in the control beam the largest crack exceeded 0.3 mm at only 59.8 kN load. Under shear loading, while the influence of the cover on structural capacity was minimal, it notably improved post-peak ductility and energy dissipation. Interface delamination was not observed in both cases. The results of the current study demonstrate the potential of delivering the self-healing mechanism precisely where it is most needed, which presents a scalable and economically viable strategy for integrating self-healing technology into standard construction practices.

An asphalt joint is formed when a fresh mix is laid and compacted next to an existing layer, brings about temperature difference during compaction, and therefore requires extra care in quality control and expose to higher cracking risks. Self-healing asphalt aims to stimulate the healing capacity of asphalt mixture and prolong its service life. The main objective of this study is to develop and optimize a calcium alginate capsules healing system for an asphalt joint mix. Capsules following two different self-healing concepts were prepared, namely conventional alginate capsules and conductive alginate capsules. Microscopy, Computed Tomography (CT) and Thermogravimetry analysis (TGA) were used to investigate the performance of alginate capsules. The results show that both types of capsules have a porous structure and a stable performance under high temperature, and therefore potentially survive from the asphalt mixing and production process. These capsules will be implemented and evaluated in full asphalt mix in future research.

The article ‘Effect of matrix self-healing on the bond-slip behavior of micro steel fibers in ultra-high-performance concrete’, written by Salam Al-Obaidi, Shan He, Erik Schlangen and Liberato Ferrara, was originally published in volume 56, issue 9, article 161 without Open Access.